Pages that link to "Item:Q4975400"
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The following pages link to Variable Selection in Nonparametric Classification Via Measurement Error Model Selection Likelihoods (Q4975400):
Displaying 15 items.
- Statistical inference on restricted linear regression models with partial distortion measurement errors (Q318978) (← links)
- Nonparametric independence screening via favored smoothing bandwidth (Q1643789) (← links)
- Nearest neighbor estimates of regression (Q1658417) (← links)
- Boosting in the Presence of Outliers: Adaptive Classification With Nonconvex Loss Functions (Q4962433) (← links)
- Univariate measurement error selection likelihood for variable selection of additive model (Q5023864) (← links)
- Efficient kernel-based variable selection with sparsistency (Q5037806) (← links)
- (Q5240870) (← links)
- A General Framework of Nonparametric Feature Selection in High-Dimensional Data (Q6079788) (← links)
- Variable selection for nonparametric quantile regression via measurement error model (Q6120382) (← links)
- Automatic structure recovery for generalized additive models (Q6180914) (← links)
- High-dimensional local linear regression under sparsity and convex losses (Q6200896) (← links)
- Logistic regression error-in-covariate models for longitudinal high-dimensional covariates (Q6541522) (← links)
- A Unified Approach to Variable Selection for Partially Linear Models (Q6552549) (← links)
- Can’t Ridge Regression Perform Variable Selection? (Q6631887) (← links)
- A novel block-coordinate gradient descent algorithm for simultaneous grouped selection of fixed and random effects in joint modeling (Q6652620) (← links)
